Stochastic determination of optimal wavelet compression strategies

Donald E. Waagen; Jeffrey D. Argast; John R. McDonnell

doi:10.1117/12.185927

16 September 1994 Stochastic determination of optimal wavelet compression strategies

Donald E. Waagen, Jeffrey D. Argast, John R. McDonnell

Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/10.1117/12.185927
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States

Abstract

Wavelet theory provides an attractive approach to signal and image compression. This work investigates a new wavelet transform coefficient selection approach for efficient image compression. For a desired image compression ratio (50:1), wavelet scale thresholds are derived via a multiagent stochastic optimization process. Previous work has demonstrated an interscale relationship between the stochastically optimized wavelet coefficient thresholds. Based on the experimental results, a deterministic wavelet coefficient selection criteria is hypothesized and the constants of the equation are statistically derived. Experimental results of the stochastic optimization and deterministic approaches are compared and contrasted with results from previously published wavelet coefficient threshold strategies.

Citation Download Citation

Donald E. Waagen, Jeffrey D. Argast, and John R. McDonnell "Stochastic determination of optimal wavelet compression strategies", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); https://doi.org/10.1117/12.185927

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